基于灰色关联度的电机故障诊断

Based on Electrical Machine Fault Diagnosis of Gray Relevance

感应电机在工农业的发展中占有举足轻重的地位,感应电机的故障诊断至关重要。而灰色理论本身在少数据,弱条件情况下也可以达到高精度的诊断结果,所以,通过感应电机垂直方向的震动数据为原始基础,通过小波包分解成能量比后进行标准数据模型建立,最后,通过灰色关联度分析判断电机故障类型。分析表明,在数据量不大的情况下,灰色关联度分析是针对感应电机故障诊断的一个简单有效的方法。

Induction motor plays a significant role in the development of industry and agriculture,so the fault diagnosis of induction motor is of crucial importance.And gray correlation theory itself can achieve high precision of diagnosis in the circumstance of less data and weak conditions.So in this paper,it uses the vibration data from vertical direction of induction motor as the original foundation,and then uses wavelet packet decomposition to make data into energy ratio to establish the standard data model.At last,use grey correlation analysis to determine motor fault types.The analyses show that grey correlation analysis is a simple and effective method for induction motor fault diagnosis in the case that the data volume is not big.